Microsoft Silicon, Cloud Hardware, and Infrastructure Engineering (SCHIE) is the team behind Microsoft’s expanding Cloud Infrastructure and responsible for powering Microsoft’s “Intelligent Cloud” mission. SCHIE delivers the core infrastructure and foundational technologies for Microsoft's over 200 online businesses including Bing, MSN, Office 365, Xbox Live, Teams, OneDrive, and the Microsoft Azure platform globally with our server and data center infrastructure, security and compliance, operations, globalization, and manageability solutions. Our focus is on smart growth, high efficiency, and delivering a trusted experience to customers and partners worldwide and we are looking for passionate engineers to help achieve that mission.
As Microsoft's cloud business continues to grow the ability to deploy new offerings and hardware infrastructure on time, in high volume with high quality and lowest cost is of paramount importance. To achieve this goal, the CHSE (Cloud Hardware Systems Engineering) team is instrumental in defining and delivering operational measures of success for hardware manufacturing, improving the planning process, quality, delivery, scale and sustainability related to Microsoft cloud hardware. We are looking for experienced engineers with a dedicated passion for customer focused solutions, insight and industry knowledge to envision and implement future technical solutions that will manage and optimize the Cloud infrastructure.
We are looking for a Principal Platform Power and Performance (PnP) Engineer to join the team.
Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.
Responsibilities
- Lead platform power and performance strategy for next-generation Microsoft AI compute platforms, driving industry-leading performance-per-watt, scalability, efficiency, and total cost of ownership (TCO).
- Provide technical leadership and mentorship for a team of highly skilled engineers while leading cross-functional initiatives that solve complex platform power, performance, and efficiency challenges.
- Partner with business, architecture, silicon, firmware, hardware, validation, operating systems, manufacturing, and customer engineering teams to define requirements and deliver optimized platform solutions.
- Drive silicon and platform power-performance architecture, including workload characterization, power management features, frequency/voltage optimization, memory subsystem efficiency, accelerator utilization, and system-level performance tuning.
- Analyze and optimize interactions between silicon, power delivery, thermal solutions, firmware, operating systems, and datacenter infrastructure to maximize performance, efficiency, reliability, and operational scalability.
- Lead power-performance characterization, profiling, and benchmarking across Azure datacenter deployments using customer workloads, AI training and inference applications, and synthetic benchmarks to guide data-driven design decisions.
- Influence future silicon and platform roadmaps through deep analysis of workload behavior, performance bottlenecks, power efficiency opportunities, and emerging AI infrastructure requirements.
- Communicate technical strategies, tradeoffs, and recommendations to engineering leadership and executive stakeholders, driving alignment across organizations and accelerating delivery of next-generation AI infrastructure.
Qualifications
Required Qualifications:
- Master's Degree in Electrical Engineering, Computer Engineering, Mechanical Engineering, or related field AND 7+ years technical engineering experience OR Bachelor's Degree in Electrical Engineering, Computer Engineering, Mechanical Engineering, or related field AND 8+ years technical engineering experience OR equivalent experience
- 8+ years of relevant experience in compute and/or AI systems/platforms design and development.
- 8+ years of experience with SoC, CPU, GPU, or AI accelerator architectures, including power management, performance analysis, memory subsystems, interconnects, power delivery, and thermal solutions.
- 8+ years of experience collaborating across hardware, firmware, operating systems, silicon architecture, and validation engineering teams to deliver platform solutions.
Other Requirements:
Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include but are not limited to the following specialized security screenings:
- Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud Background Check upon hire/transfer and every two years thereafter.
Preferred Qualifications:
- Experience with hyperscale cloud infrastructure, large-scale AI compute platforms, and datacenter operations.
- Experience with custom silicon, AI accelerators, and silicon bring-up from pre-silicon validation through production deployment.
- Knowledge of server architecture, power delivery systems, and liquid cooling technologies.
- Experience with workload characterization, profiling, benchmarking, and performance analysis for AI/ML workloads in large-scale datacenter environments.
- Experience optimizing performance, efficiency, and performance-per-watt across hardware and software systems.
- Experience leading cross-functional technical initiatives spanning multiple engineering disciplines.
#SCHIE #CHSE #azurehwjobs
Hardware Engineering IC5 - The typical base pay range for this role across the U.S. is USD $142,800 - $274,800 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $188,000 - $304,200 per year.
Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
https://careers.microsoft.com/us/en/us-corporate-pay
This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.
Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.
Microsoft Mountain View, California, USA Office
1065 La Avenida, Mountain View, CA 94043, Mountain View, United States, 94043
Microsoft Palo Alto, California, USA Office
Palo Alto, United States
Microsoft San Francisco, California, USA Office
835 Market Street, Suite 700, San Francisco, CA 94103, San Francisco, United States, 94103
Microsoft San Jose, California, USA Office
San Jose, United States
Microsoft Sunnyvale, California, USA Office
Sunnyvale, United States
Similar Jobs
What you need to know about the San Francisco Tech Scene
Key Facts About San Francisco Tech
- Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Google, Apple, Salesforce, Meta
- Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
- Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine
